1) Structural growth trajectories and rates of change in the first 3 months of infant brain development.

Holland Dominic et al, JAMA Neurol.2014:71(10)



The very early postnatal period witnesses extraordinary rates of growth, but structural brain development in this period has largely not been explored longitudinally. Such assessment may be key in detecting and treating the earliest signs of neurodevelopmental disorders.


To assess structural growth trajectories and rates of change in the whole brain and regions of interest in infants during the first 3 months after birth.


Whole-brain volume at birth was approximately one-third of healthy elderly brain volume, and did not differ significantly between male and female infants (347 388 mm3 and 335 509 mm3, respectively, P = .12). The growth rate was approximately 1%/d, slowing to 0.4%/d by the end of the first 3 months, when the brain reached just more than half of elderly adult brain volume. Overall growth in the first 90 days was 64%.There was a significant age-by-sex effect leading to widening separation in brain sizes with age between male and female infants (with male infants growing faster than females by 200.4 mm3/d, SE = 67.2, P = .003). Longer gestation was associated with larger brain size (2215 mm3/d, SE = 284, P = 4×10-13). The expected brain size of an infant born one week earlier than average was 5% smaller than average; at 90 days it will not have caught up, being 2% smaller than average. The cerebellum grew at the highest rate, more than doubling in 90 days, and the hippocampus grew at the slowest rate, increasing by 47% in 90 days.There was left-right asymmetry in multiple http://www.gulfportpharmacy.com regions of interest, particularly the lateral ventricles where the left was larger than the right by 462 mm3 on average (approximately 5% of lateral ventricular volume at 2 months). We calculated volume-by-age percentile plots for assessing individual development


Normative trajectories for early postnatal brain structural development can be determined from magnetic resonance imaging and could be used to improve the detection of deviant maturational patterns indicative of neurodevelopmental disorders